Oculomic stratification of COVID-19 patients’ intensive therapy unit admission status and mortality by retinal morphological findings

To investigate if retinal thickness has predictive utility in COVID-19 outcomes by evaluating the statistical association between retinal thickness using OCT and of COVID-19-related mortality. Secondary outcomes included associations between retinal thickness and length of stay (LoS) in hospital. In this retrospective cohort study, OCT scans from 230 COVID-19 patients admitted to the Intensive Care Unit (ITU) were compared with age and gender-matched patients with pneumonia from before March 2020. Total retinal, GCL + IPL, and RNFL thicknesses were recorded, and analysed with systemic measures collected at the time of admission and mortality outcomes, using linear regression models, Pearson’s R correlation, and Principal Component Analysis. Retinal thickness was significantly associated with all-time mortality on follow up in the COVID-19 group (p = 0.015), but not 28-day mortality (p = 0.151). Retinal and GCL + IPL layer thicknesses were both significantly associated with LoS in hospital for COVID-19 patients (p = 0.006 for both), but not for patients with pneumonia (p = 0.706 and 0.989 respectively). RNFL thickness was not associated with LoS in either group (COVID-19 p = 0.097, pneumonia p = 0.692). Retinal thickness associated with LoS in hospital and long-term mortality in COVID-19 patients, suggesting that retinal structure could be a surrogate marker for frailty and predictor of disease severity in this group of patients, but not in patients with pneumonia from other causes.


OCT thickness analysis
Patients were grouped by eye diagnosis (before thickness analysis was completed.Diagnoses included neovascular/dry/wet age-related macular degeneration, diabetic retinopathy, primary open angle glaucoma, diabetic maculopathy, and macula oedema.

Statistics
We used univariate t test with false discovery rate correction (Benjamini-Hochberg, BH Procedure).A significance label was considered as p < 0.05.Associations with length of stay in COVID-19 patients and pneumonia control patients were estimated using linear regression, with corrected p values and variation explained (R 2 ) reported.Correlation between measures was calculated using Pearson's R correlation.In addition, Principal Component Analysis (PCA) was performed to study the variation in both cohorts.For PCA, data were normalised (standardised) using auto scaling.All analyses were performed in R (v4.2.3; R Core Team 2023) 19 .

Informed consent statement
Informed consent requirement was waived by the DeCOVID institutional ethics committee for this retrospective study.

Results
2040 COVID-19 positive patients were admitted to either the QEHB wards or ITU between December 2019 and December 2020, of which 230 patients had OCT imaging in the prior 10 years and were included in the final analysis.2581 pneumonia patients who had attended a previous ophthalmology appointment were admitted to either the QEHB wards or ITU between November 2016 and February 2020 and from this group 230 age and gender-matched patients were included in the final analysis (all admitted before March 2020) (Fig. 1, Table 1).Mortality was assessed as "all time" at any point in follow up from the date of admission (0 to 1700 days, Table 1), as well as 28-day mortality after admission.

LoS in hospital associated with retinal thickness in patients with COVID-19
Retinal and GCL + IPL layer thicknesses were both strongly associated with LoS in patients with COVID-19 (p = 0.006 for both; Table 2, Supplementary Fig. 1), but not in patients with pneumonia (p = 0.706 and 0.989 respectively; Table 2).RNFL thickness was weakly associated with LoS in hospital in the COVID-19 group (p = 0.097) but not in patients with pneumonia (p = 0.692).

LoS associated with acute inflammatory blood markers in patients with COVID-19
The LoS in hospital for patients with COVID-19 was significantly associated with blood inflammatory markers, with the strongest association for levels of peak neutrophils, WBC, and CRP levels (p < 0.001 for all measures) (Table 2, Supplementary Fig. 1), while only peak neutrophil levels were significantly associated with LoS for patients with pneumonia but not WBC or CRP levels (p = 0.003, 0.655, 0.144 respectively; Supplementary Fig. 2).NEWS was not significantly different between patients with pneumonia and patients with COVID-19 (4.38 and 4.16 respectively, p = 0.56; Table 1), suggesting similar levels of disease severity.LoS in hospital was also significantly associated with low haemoglobin and haematocrit both in patients with COVID-19 (p < 0.001) and patients with pneumonia (p < 0.001; Table 2).

Retinal thickness associated with all-time mortality in patients with COVID-19 and pneumonia, but not 28-day mortality
Most blood markers were significantly associated with all-time mortality in COVID-19 patients, with the strongest association with peak CRP level, CRP on admission, and lowest albumin level (p < 0.001 for all; Fig. 2, Table 3).Total retinal thickness was also associated with all-time mortality (p = 0.015), although GCL + IPL and RNFL thickness were not (Fig. 2, Table 3).No blood markers were significantly associated with all-time mortality in pneumonia patients (Fig. 3, Table 3), but similar to the COVID-19 group, retinal thickness was associated with all-time mortality in pneumonia patients (p = 0.024; Fig. 3, Table 3).
No retinal thickness measurements were associated with 28 day mortality in patients with either COVID-19 (retinal thickness p = 0.151, GCL + IPL p = 0.610, RNFL p = 0.480) or pneumonia (GCL + IPL p = 0.344, RNFL p = 0.813) except for total retinal thickness in patients with pneumonia, which was weakly associated with 28 day mortality (p = 0.067; Fig. 4, Table 4).The blood markers most strongly associated with 28-day mortality in COVID-19 patients were lowest albumin level, peak neutrophil count, and peak CRP (p < 0.001), while    the strongest markers for pneumonia patients were lowest albumin level and age on admission (p = 0.043 and p = 0.001 respectively, Fig. 5, Table 4).

Associations with retinal layer thicknesses in retinal diagnostic subgroups
The retinal diagnoses for which the included patients attended the ophthalmology clinic are reported in Table 1, with comparable proportions of patients with diabetic macular oedema and wet age-related macular degeneration, but a higher proportion of patients with diabetic retinopathy and glaucoma in the COVID-19 group compared to the pneumonia group.Subgroup analysis of the association between LoS and GCL+ thickness in the different retinal diagnostic groups in patients with COVID-19 revealed the same directionality of association in the diagnostic groups: other (p = 0.04), glaucoma (p = 0.05), none (p = 0.11), dry age-related macular degeneration (p = 0.57), and diabetic macular oedema (p = 0.64); but not in: diabetic retinopathy (p = 0.92) or wet age-related macular degeneration (p = 0.83).Similarly, for the association between LoS and retinal thickness, subgroup analysis revealed the same directionality of association in the diagnostic groups: none (p < 0.001), glaucoma (p = 0.009), diabetic retinopathy (p = 0.85), and wet age-related macular degeneration (p = 0.43) but not the other groups.For the association with mortality in patients with COVID-19, retinal thickness retained the same (non-significant) association in all retinal diagnostic groups except diabetic macular oedema, whilst a model could not be fit for the same subgroup analysis in patients with pneumonia.

Discussion
When analysing previously acquired structural OCT images from patients admitted to hospital with COVID-19, retinal thickness and GCL + IPL layer thickness were significantly associated with the LoS in hospital in this group of patients but not in patients with pneumonia, whilst retinal thickness was predictive of all-time but not 28 day mortality for patients with both COVID-19 and pneumonia.These findings suggest that retinal thickness could be a predictor of COVID-19 and pneumonia severity and potentially represent a marker for frailty, supporting wider associations between systemic disease and retinal signs [20][21][22][23] .Frailty is a medical syndrome which increases an individual's vulnerability to and risk of adverse health outcomes when exposed to a stressor 24 , which considers weight loss, exhaustion, low activity, slowness, and weakness in the screening process 24 .Frailty is an independent predictor of mortality in COVID-19 patients 25 , with an increased risk of mortality in frail patients who were under 65 years old as well as an increased incidence of ITU admission 26 .Frailty is a risk factor for increased susceptibility to and severity of pneumonia in adults ≥ 65 years old 27 .The severity of physical frailty assessed by the Fried phenotype (which includes physical inactivity, exhaustion, weakness, weight loss, and slow walking speed) correlated with elevated total white matter hyperintensity   and lower grey matter volume 28 .The neuroretina contains central nervous system neurons and retinal perfusion and structural changes may reflect cerebral changes in illnesses from stroke to multiple sclerosis in addition to systemic diseases such as sepsis and cardiac disease 6,29 .An association between retinal changes and frailty could therefore reflect the manifestation of multiple neurodegenerative and cardiovascular diseases.We found that retinal thickness was associated with all-time mortality in both patients with COVID-19 and pneumonia, though not 28-day mortality, which could support the ability of retinal thickness to be a marker of long-term frailty, consistent with the stronger findings in patients with COVID-19 and LoS.We were unable to control for frailty, as frailty was only recorded routinely in the COVID-19 group.Both retinal thickness and GCL + IPL thickness significantly associated with LoS in COVID-19 patients, but not in pneumonia patients.LoS is not just dependent on the medical reason for admission and can be affected by patient demographics, past medical history, treatment complexity, and complications 17 .Log regression statistics, machine learning, and data mining are all used to predict LoS with the aim to predict the level of care that may be required for the patient, although it remains a complicated area to model due to external factors 17 .As retinal thickness is associated with COVID-19 LoS, retinal assessments may be able to contribute to predictive markers for patient LoS in this group.However, retinal thickness was not associated with LoS in pneumonia patients, which may be because this group of patients was less severely ill (although NEWS was equal between the groups) or the fact that we were not able to separate community acquired and hospital acquired pneumonia, so the pneumonia patient group may be more heterogenous.During the pandemic, hospital admissions were under greater pressure than before, with the consequence that only the most severely ill and vulnerable patients were admitted 30 .The difference between COVID-19 and pneumonia patients could relate to the frailty of the patient prior to admission, with a stronger signal from retinal thickness in the frailer COVID-19 group but not in the less frail pneumonia group.Blood infection markers were also associated with LoS and all-time mortality, and therefore associate with illness severity, although these results came from blood collected during admission.Because retinal layer thicknesses showed associations with these outcomes, and the OCT images were taken before admission, retinal thickness may predict these outcomes and susceptibility to severe disease.
There was a higher number of patients with COVID-19 who had chronic renal failure compared to patients with pneumonia.A recent study found that patients with chronic kidney disease had retinal and choroidal thinning on OCT compared with healthy volunteers 31 , with similar results shown in late-stage chronic kidney disease in another study 32 .Renal failure also represents a risk for severe COVID-19, which may also cause acute kidney injury.It is therefore unsurprising that renal failure would be more common and EGFR lower in patients with COVID-19 than in patients with pneumonia.Many other systemic diseases may also manfest in retinal thickness or perfusion changes 6 .The PCA analysis examines the contribution of each included predictor independently, and it would be informative in future larger studies to examine the interaction between renal failure, retinal thickness and disease susceptibility.
The associations between retinal thickness, LoS and mortality were present across most diagnostic groups, although the study was most likely not powered for these subgroup analyses.In particular retinal thickness associated with LoS and mortality in patients with no retinal diagnosis, and glaucoma, but not in patients with age-related macular degeneration or diabetic maculopathy, which may reflect greater variability in the data caused by retinal oedema in these cohorts.

Conclusions
The associations between retinal thickness and LoS in hospital in COVID-19 patients, and retinal thickness and all-time mortality in both patients with COVID-19 and those with pneumonia, suggests that retinal structure could be a marker of frailty and a predictor of disease severity in this group.

Figure 2 .
Figure 2. Boxplots of significant associations with all time mortality in patients with COVID-19.The green boxplots represent patients who survived, the red boxplots represent patients who died.Each black dot represents a patient with COVID-19.The yellow rhombus represents the mean value of the distribution.CRP C-reactive protein, WBC white blood cells, EGFR estimated glomerular filtration rate.

Figure 3 .
Figure 3. Boxplots to show associations with all time mortality of patients with pneumonia and significant markers.The green boxplots represent patients who survived, the red boxplots represent patients who died.Each black dot represents a patient with pneumonia.The yellow rhombus represents the mean value of the distribution.

Figure 4 .
Figure 4. Boxplots to show associations with 28-day mortality of patients with COVID-19 and significant markers.The green boxplots represent patients who survived, the red boxplots represent patients who died.Each black dot represents a patient with COVID-19.The yellow rhombus represents the mean value of the distribution.CRP C-reactive protein, WBC white blood cells.

Figure 5 .
Figure 5. Boxplots to show associations with 28-day mortality of patients with pneumonia and significant markers.The green boxplots represent patients who survived, the red boxplots represent patients who died.Each black dot represents a patient with pneumonia.The yellow rhombus represents the mean value of the distribution.

Table 1 .
Patient demographics table for COVID-19 and pneumonia groups.Demographics and clinical characteristics of the participants included in the study given as mean (standard deviation).P-values of < 0.05 are considered significant.N number, SD standard deviation, COPD chronic obstructive pulmonary disorder, CRP C-reactive protein, HCT haematocrit, HGB haemoglobin, WBC white blood cells, ALB albumin, EGFR estimated glomerular filtration rate.

Table 2 .
Associations with length of stay in patients with COVID-19 and patients with pneumonia.Rows in bold text represent statistically significant differences in measures, where p ≤ 0.05.SD standard deviation, GCL ganglion cell layer, IPL inner plexiform layer, RNFL retinal nerve fibre layer, CRP C-reactive protein, WBC white blood cells, EGFR estimated glomerular filtration rate.* p < 0.05.

Table 3 .
Associations with all-time mortality.Rows in bold text represent statistically significant differences in measures, where p ≤ 0.05.FDR false discovery rate, GCL ganglion cell layer, IPL inner plexiform layer, RNFL retinal nerve fibre layer, CRP C-reactive protein, WBC white blood cells, EGFR estimated glomerular filtration rate.

Table 4 .
Associations with 28-day mortality.Rows in bold text represent statistically significant differences in measures, where p ≤ 0.05.FDR false discovery rate, GCL ganglion cell layer, IPL inner plexiform layer, RNFL retinal nerve fibre layer, CRP C-reactive protein, WBC white blood cells, EGFR estimated glomerular filtration rate.